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2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)最新文献

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Change detection algorithm for land cover in grid systems 网格系统中土地覆盖变化检测算法
2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2013-10-24 DOI: 10.1109/ICCP.2013.6646132
Mihaela-Catalina Nita, F. Moldoveanu, V. Asavei
{"title":"Change detection algorithm for land cover in grid systems","authors":"Mihaela-Catalina Nita, F. Moldoveanu, V. Asavei","doi":"10.1109/ICCP.2013.6646132","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646132","url":null,"abstract":"Natural phenomena, like season changing, Vulcan eruptions, flooding, or even non-natural ones, like human intervention, may lead to a completely new image of the Earth. However, one thing is sure: the Earth's surface is permanently changing and the need for disaster prevention is immediate. In this context, one of the main challenges is to provide fast and accurate information; imagine PBs of data coming from Satellites every day. The data processing has to be fast and accurate, in order to overcome any disaster. In this paper we analyze the advantages of a distributed change detection algorithm in terms of speedup.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132606677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Towards combining functional requirements tests and unit tests as a preventive practice against software defects 将功能需求测试和单元测试结合起来，作为对软件缺陷的预防性实践
2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2013-10-24 DOI: 10.1109/ICCP.2013.6646121
Raluca Dudila, I. A. Letia
{"title":"Towards combining functional requirements tests and unit tests as a preventive practice against software defects","authors":"Raluca Dudila, I. A. Letia","doi":"10.1109/ICCP.2013.6646121","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646121","url":null,"abstract":"During the last decade, software testing has gained increased popularity and awareness. Despite this fact, major companies around the world have already started to eliminate the process of software testing as a singular activity and have included it within the other steps of the software life-cycle. By adhering to this tendency, this article concentrates on exploring two existing white box and black box testing techniques together with a method by which they can be combined and applied during code creation in order to minimize the debugging effort at a later point in time. An open source software program written in .NET was chosen for demonstrating the proposed gray-box method and a small analysis on the use-case coverage was made.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114870943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Image context classification based on visual codebook feature boosting 基于视觉码本特征增强的图像上下文分类
2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2013-10-24 DOI: 10.1109/ICCP.2013.6646096
A. Costea, S. Nedevschi
{"title":"Image context classification based on visual codebook feature boosting","authors":"A. Costea, S. Nedevschi","doi":"10.1109/ICCP.2013.6646096","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646096","url":null,"abstract":"This paper presents a method for classifying the context of images. The context of an image can be classified as indoor, outdoor or a more specific scene category. Several state of the art methods use visual codebooks in order to construct global image descriptors and classify the latter using a Support Vector Machine (SVM) classifier. This paper proposes boosting over visual codebook features as an alternative to SVM classification. The boosting based approach has several advantages: fast training and classification time, no need for classifier parameter tuning, efficient combination of different descriptor types, small classifier models. The proposed method performs well on large datasets with many classes and provides state of the art results.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"148 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130023263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Contradiction detection between opinions: From a big data perspective 观点之间的矛盾检测:基于大数据的视角
2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2013-10-24 DOI: 10.1109/ICCP.2013.6646118
B. Vancea, A. Marchis, M. Dînsoreanu, R. Potolea
{"title":"Contradiction detection between opinions: From a big data perspective","authors":"B. Vancea, A. Marchis, M. Dînsoreanu, R. Potolea","doi":"10.1109/ICCP.2013.6646118","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646118","url":null,"abstract":"This paper offers a solution to the problem of detecting contradictions among opinions on the same topic. The opinions are extracted from a large number of unstructured documents and stored in a structured format. Due to the increase in data available for analysis, we focus on providing a storage/retrieval and analysis solution suitable for managing large quantities of data while maintaining the speed and reliability present in smaller scale systems. Our approach consists in building a distributed system able to scale horizontally with the increase in input data without any significant performance decay. We represent opinions in a tuple based structured model, more suitable for retrieval and analysis. This approach allows us to formalize an algorithm for detecting contradictions between opinion tuples. Furthermore, we present a method for improving the recall of the system by using synonyms for the opinion target to expand the set of possible contradicting opinions. Our main focus is to optimize the structure of the opinion tuple to provide the best retrieval time and to allow for a simple, structured approach for detecting contradictions.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122503479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Robust background removal in 4D Studio images 在4D工作室图像鲁棒的背景去除
2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2013-10-24 DOI: 10.1109/ICCP.2013.6646087
Corina Blajovici, Zsolt Jankó, D. Chetverikov
{"title":"Robust background removal in 4D Studio images","authors":"Corina Blajovici, Zsolt Jankó, D. Chetverikov","doi":"10.1109/ICCP.2013.6646087","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646087","url":null,"abstract":"In this paper we discuss background removal techniques developed for the 4D Reconstruction Studio at MTA SZTAKI. The 4D Studio enables creation of dynamic 3D models of real objects and actors. Robust foreground segmentation is a key element for 4D reconstruction, since the visual quality of the 3D model highly depends on the precision of the extracted silhouette. We present our novel solution for background removal based on exploiting the background colour in a robust manner. We also perform an analysis of shadow detection methods using different colour spaces, with the motivation of determining which colour representation is more suitable for shadow detection in a 4D Studio.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128939989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Sentiment polarity identification using machine learning techniques 使用机器学习技术识别情感极性
2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2013-10-24 DOI: 10.1109/ICCP.2013.6646079
Raluca Chiorean, M. Dînsoreanu, Daciana-Ioana Faloba, R. Potolea
{"title":"Sentiment polarity identification using machine learning techniques","authors":"Raluca Chiorean, M. Dînsoreanu, Daciana-Ioana Faloba, R. Potolea","doi":"10.1109/ICCP.2013.6646079","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646079","url":null,"abstract":"The paper proposes an improved approach to the problem of sentiment polarity identification. Its main focus is on identifying and extracting the relevant information from natural language texts in order to obtain a set of best predictive features to be used for the classification task. Our approach of determining the polarity of a text consists of a combination of several processing techniques that obtains an efficient set of appropriate information for the underlying text. Among techniques, we have considered pruning the feature set to discard features without polarity or with less discriminative power, since their presence tend to mislead the learning process. Moreover, using word co-occurrence techniques, new composed bi-grams with high discriminative power are added which enhances the classification process. The best results are obtained using different combinations of techniques, depending on the dataset's homogeneity. On a homogeneous dataset, the performance in terms of precision is approximately 88% and, in terms of recall, a value of 93% is reached. In the case of a diverse dataset, the performance attained is 100%.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131648274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Performance prediction for parallel applications running on HPC architectures through Petri net modelling and simulation 基于Petri网建模与仿真的高性能计算架构并行应用性能预测
2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2013-10-24 DOI: 10.1109/ICCP.2013.6646119
Ion Dan Mironescu, L. Vintan
{"title":"Performance prediction for parallel applications running on HPC architectures through Petri net modelling and simulation","authors":"Ion Dan Mironescu, L. Vintan","doi":"10.1109/ICCP.2013.6646119","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646119","url":null,"abstract":"The paper presents the development of a model and a simulation technique for the prediction of the performance of a concurrent application running on a HPC architecture. Models for the hardware and software were developed using the Coloured Petri Net formalism and then coupled for the simulation. Timed simulations were performed in the Coloured Petri Net tools environment and in the Charm++ respectively the BigSim simulator. The results of both simulations for the same optimization problem show similar trends.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127322560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Speed estimation for scene objects using stereo visual odometry methods 基于立体视觉里程计方法的场景物体速度估计
2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2013-10-24 DOI: 10.1109/ICCP.2013.6646088
Catalin Golban, S. Nedevschi
{"title":"Speed estimation for scene objects using stereo visual odometry methods","authors":"Catalin Golban, S. Nedevschi","doi":"10.1109/ICCP.2013.6646088","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646088","url":null,"abstract":"This paper proposes a novel method to determine the speed of the surrounding vehicles in traffic scenarios. Relying on the video information obtained from a stereo camera mounted on a moving vehicle, we first determine the vehicle ego motion based on static scene features then we determine the relative motion between objects based on features situated on the moving objects. For robustness to false feature matches everything is plugged into a multi-RANSAC framework. The novelty of the method consist in the fact that the relative motion between the objects can be determined with the same algorithm that was previously used for ego motion estimation, the only difference consisting in the geometric constraints that are imposed to the subset of point features considered for inliers set detection and evaluation. Also, the proposed method does not rely on the fact that objects are detected previously and it does not detect the objects.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125064345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A low-cost stereo system for 3D object recognition 用于三维物体识别的低成本立体系统
2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2013-10-24 DOI: 10.1109/ICCP.2013.6646095
F. Oleari, Dario Lodi Rizzini, S. Caselli
{"title":"A low-cost stereo system for 3D object recognition","authors":"F. Oleari, Dario Lodi Rizzini, S. Caselli","doi":"10.1109/ICCP.2013.6646095","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646095","url":null,"abstract":"In this paper, we present a low-cost stereo vision system designed for object recognition with FPFH point feature descriptors. Image acquisition is performed using a pair of consumer market UVC cameras costing less than 80 Euros, lacking synchronization signal and without customizable optics. Nonetheless, the acquired point clouds are sufficiently accurate to perform object recognition using FPFH features. The recognition algorithm compares the point cluster extracted from the current image pair with the models contained in a dataset. Experiments show that the recognition rate is above 80% even when the object is partially occluded.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124497140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 18
Using community detection for sentiment analysis 使用社区检测进行情感分析
2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2013-10-24 DOI: 10.1109/ICCP.2013.6646080
Paul Parau, A. Stef, C. Lemnaru, M. Dînsoreanu, R. Potolea
{"title":"Using community detection for sentiment analysis","authors":"Paul Parau, A. Stef, C. Lemnaru, M. Dînsoreanu, R. Potolea","doi":"10.1109/ICCP.2013.6646080","DOIUrl":"https://doi.org/10.1109/ICCP.2013.6646080","url":null,"abstract":"This paper presents a system for identifying communities in networks built based on opinions and social data. We show how we can build graphs from opinions and social interactions and how we identify the community structure of these graphs. We handle both types of data: one-dimensional and multidimensional. As community detection method, we use the Infomap algorithm. The dimensions considered for identifying communities are one or many opinions and social attributes. We show how contradictions can be detected using the identified communities.","PeriodicalId":380109,"journal":{"name":"2013 IEEE 9th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122446618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
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